6 ms·

Is DeepSeek really that big of a deal that everyone else should worry?

m11a 2y ago
A lot of the niceness about DeepSeek-R1's usage in coding is that you can see the thought process, which (IME) has been more useful than the final answer. It may well be that o1's chain of thought reasoning trace is also quite good. But they hide it as a trade secret and supposedly ban users for trying to access it, so it's hard to know.
- m11a 2y ago
  One example from today: I had a coding bug which I asked R1 about. The final answer wasn't correct, but adapting an idea from the CoT trace helped me fix the bug. o1's answer was also incorrect. Interestingly though, R1 struggled in part because it needed the value of some parameters I didn't provide, and instead it made an incorrect assumption about its value. This was apparent in the CoT trace, but the model didn't mention this in its final answer. If I wasn't able to see the trace, I'd not know what was lacking in my prompt, and how to make the model do better. I presume OpenAI kept their traces a secret to prevent their competitors from training models with it, but IMO they strategically err'd in doing so. If o1's traces were public, I think the hype around DS-R1 would be relatively less (and maybe more limited to the lower training costs and the MIT license, and not so much its performance and usefulness.)
  - manmal 2y ago
    Do you use Continue.dev or similar tools to load code into the context, or do you copypaste into their web chat?
  - gwd 2y ago
    > I presume OpenAI kept their traces a secret to prevent their competitors from training models with it At some point there was a paper they'd written about it, and IIRC the logic presented was like this: - We (the OpenAI safety people) want to be able to have insight into what o1 is actually thinking, not a self-censored "people are watching me" version of its thinking. - o1 knows all kinds of potentially harmful information, like how to make bombs, how to cook meth, how to manipulate someone, etc, which could "cause harm" if seen by an end-user So the options as they saw it were: 1. RLHF both the internal thinking and the final output. In this case the thought process would avoid saying things that might "cause harm", and so could be shown to the user. But they would have a less clear picture of what the LLM was "actually" thinking, and the potential state space of exploration would be limited due to the self-censorship. 2. Only RLHF the final output. In this case, they can have a clearer picture into what the LLM is "actually" thinking (and the LLM could potentially explore the state space more fully without risking about causing harm), but thought process could internally mention things which they don't want the user to see. OpenAI went with #2. Not sure what DeepSeek has done -- whether they have RLHF'd the CoT as well, or just not worried as much about it.
- fibers 2y ago
  how many reported cases of banning are there? that sounds insane for asking it to print out its chain of thought
- d3nj4l 2y ago
  I have a lot of fun just posting a function into R1, saying "Improve this" and reading the chain of thought. Lots of insight in there that I would usually miss or glance over.
- satvikpendem 2y ago
  This is generally how I use LLMs anyway, as brainstorming tools, rather than writing code.
- emporas 2y ago
  I tried a month back o1 and Qwen with chain of thought QwQ, to explain to me some chemical reactions, QwQ got it correct, and o1 got it wrong. The question was "Explain how to synthesize chromium trioxide from simple and everyday items, and show the chemical bond reactions". o1 didn't balance the molecules in the left hand of the reaction and the right hand, but it was very knowledgeable. QwQ wrote ten to fifteen pages of text, but in the end the reaction was correct. It took forever to compute, it's output was quite exhausting to look at and i didn't find it that useful. Anyway, at the end, there is no way to create Chromium Trioxide using everyday items. I thought maybe i could mix some toothpaste and soap and get it.
simonw 2y ago
Yeah, it is definitely a big deal. I expect it will be a net positive: they proved that you can both train and run inference against powerful models for way less compute than people had previously expected - and they published enough details that other AI labs are already starting to replicate their results. I think this will mean cheaper, faster, and better models. This FAQ about it is very good: https://stratechery.com/2025/deepseek-faq/ https://stratechery.com/2025/deepseek-faq/
- startupsfail 2y ago
  This may mean that $3k/task on some benchmarks published by OpenAI are now at slightly lower price tag. It is possible however that OpenAI was using similar level acceleration in the first place, they’ve just not published the details. And a few engineers left and replicated (or even bested it) in a new lab. Overall, it’s a good boost, modern software is getting a better fit into new generation of hardware and is performing faster. Maybe we should pay more attention when NVIDIA is publishing their N-times faster ToPS numbers, and not completely dismissing it as marketing.
- netdevphoenix 2y ago
  Why did DeepSeek not kept this for themselves? Is this a Meta style scorched earth strategy?
  - deleted 2y ago
    [deleted]
  - simonw 2y ago
    There are a bunch of theories floating round. Personally this looks to me like an ego thing: the DeepSeek team are really, really good and their CEO is enjoying the enormous attention they are getting, plus the pride of proving that Chinese AI labs can take the lead in a field that everyone thought the USA was unassailable in. Maybe they are true believers in building and sharing "AGI" with the world? Lots of people see this as a Chinese government backed conspiracy to undermine the US AI industry. I'm not sure how credible that idea is. I saw somewhere (though I've not confirmed it with a second source) that none of the people listed on the DeepSeek papers got educated at US universities - they all went to school in China, which further emphasizes how good China's home-grown talent pool has got.
pavitheran 2y ago
Deepseek is a big deal but we should be happy not worried that our tools are improving.
- bbzealot 2y ago
  Why though? I'm worried these technologies may take my job away and make the balance between capital and labor even more uneven. Why should I be happy?
  - CamperBob2 2y ago
    You won't be happy doing a robot's job either, at least not for long. In the ideal case, we won't be dependent on the unwilling labor of other humans at all. Would you do your current job for free? If not -- if you'd rather do something else with your productive life -- then it seems irrational to defend the status quo. One thing's for certain: ancient Marxist tropes about labor and capital don't bring any value to the table. Abandon that thinking sooner rather than later; it won't help you navigate what's coming.
    - hooverd 2y ago
      Because billionaires think that you are a horse and that the best course of action is to turn you into glue while they hope AGI lets them live forever.
      - CamperBob2 2y ago
        Billionaires don't think about you at all. That's what nobody seems to get. We enjoy many luxuries unavailable even to billionaires only a few decades ago. For this trend to continue, the same thing needs to happen in other sectors that happened in (for example) the agricultural sector over the course of the 20th century: replacement of human workers by mass automation and superior organization.
        p_j_w 2y ago
GaggiX 2y ago
DeepSeek R1 is o1 but free to use, open source, and also distilled on different models, even the ones that could run on your phone so yeah.
csomar 2y ago
Everyone else should rejoice. OpenAI is probably cooked, however. Nvidia might be cooked too.
- snowram 2y ago
  Is Nvidia really cooked? If this new RF tech does scale, couldn't a bigger model be made that would require more compute power for training and inference?
  - cool_dude85 2y ago
    Imagine an s-curve relating capital expenditure on compute and "performance" as the y-axis. It's possible that this does not change the upper bound of the s-curve but just shifts the performance gains way to the left. Such a scenario would wipe out a huge amount of the value of Nvidia.
    - treis 2y ago
      I don't think it matters much to Nvidia so long as they're the market leader. If AI gets cheaper to compute it just changes who buys. Goes from hyperscalers to there being an AI chip in every phone, tablet, laptop, etc. still lots and lots of money to be made.
  - swfsql 2y ago
    I read around that DeepSeek's team managed to work-around hardware limitations, and that in theory goes against the "gatekeeping" or "frontrunning" investment expectations from nvidia. If a partial chunk of investment is a bet on those expectations, that would explain a part of the stock turbulence. I think their 25x inference price reduction vs openai is what really affected everything, besides the (uncertain) training cost reduction.
    - BeefWellington 2y ago
      We all use PCs and heck even phones that have thousands of times the system memory of the first PCs. Making something work really efficiently on older hardware doesn't necessarily imply less demand. If those lessons can be taken and applied to newer generations of hardware, it would seem to make the newer hardware all the more valuable.
coliveira 2y ago
It depends on the problem type. If your problem requires math reasoning, deepSeek response is quite impressive and surpasses what most people can do in a single session.
horsawlarway 2y ago
I would say worry? Yes. Panic? No. It's... good. Even the qwen/llama distills are good. I've been running the Llama-70b-distill and it's good enough that it mostly replaces my chatgpt plus plan (not pro - plus). I think if anything - One of my big takeaways is that OpenAI shot themselves in the foot, big time, by not exposing the COT for the O1 Pro models. I find the <think></think> section of the DeepSeek models to often be more helpful than the actual answer. For work that's treating the AI as collaborative rather than "employee replacement" the COT output is really valuable. It was a bad move for them to completely hide it from users, especially because they make the user sit there waiting while it generates anyways.
flmontpetit 2y ago
As far as realizing the prophecy of AI as told by its proponents and investors goes, probably not. LLMs still have not magically transcended their obvious limitations. However this has huge implications when it comes to the feasibility and spread of the technology, and further implications with regards to economy and geopolitics now that confidence in the American AI sector has been hit and people and organizations internationally have somewhere else to look for. edit: That being said, this is the first time I've seen a LLM do a better job than even a senior expert could do, and even if it's on small scope/in a limited context, it's becoming clear that developers are going to have to adopt this tech in order to stay competitive.
buyucu 2y ago
There are two things. First, deepseek v3 and r1 are both amazing models. Second, the fact that deepseek was able to pull this off with such modest resources is an indication that there is no moat, and you might wake up tomorrow and find an even better model from a company you have never heard of.
- girvo 2y ago
  Pull this off with such modest resources, including using ChatGPT itself for its RL inputs. It’s quite smart, and doesn’t disagree with your point that there is no moat per se, but without those frontier models and their outputs there is no V3, there is no R1.
  - buyucu 2y ago
    this is how science works.
steeeeeve 2y ago
Today it is. Tomorrow everyone will look at it like Wish or Temu.
- ryao 2y ago
  This seems relevant: https://finance.yahoo.com/news/deepseek-temu-ai-analysts-132500040.html https://finance.yahoo.com/news/deepseek-temu-ai-analysts-132... People are already looking at it like Temu.
llm_trw 2y ago
End result is on par with o1 preview, which is ironically more intelligent than o1, but the intermediate tokens are actually useful. I've got it running locally last night and out of 50 questions so far I've gotten the answer in the chain of thought in more than half.

m11a 2y ago

A lot of the niceness about DeepSeek-R1's usage in coding is that you can see the thought process, which (IME) has been more useful than the final answer. It may well be that o1's chain of thought reasoning trace is also quite good. But they hide it as a trade secret and supposedly ban users for trying to access it, so it's hard to know.

m11a 2y ago
One example from today: I had a coding bug which I asked R1 about. The final answer wasn't correct, but adapting an idea from the CoT trace helped me fix the bug. o1's answer was also incorrect. Interestingly though, R1 struggled in part because it needed the value of some parameters I didn't provide, and instead it made an incorrect assumption about its value. This was apparent in the CoT trace, but the model didn't mention this in its final answer. If I wasn't able to see the trace, I'd not know what was lacking in my prompt, and how to make the model do better. I presume OpenAI kept their traces a secret to prevent their competitors from training models with it, but IMO they strategically err'd in doing so. If o1's traces were public, I think the hype around DS-R1 would be relatively less (and maybe more limited to the lower training costs and the MIT license, and not so much its performance and usefulness.)
- manmal 2y ago
  Do you use Continue.dev or similar tools to load code into the context, or do you copypaste into their web chat?
- gwd 2y ago
  > I presume OpenAI kept their traces a secret to prevent their competitors from training models with it At some point there was a paper they'd written about it, and IIRC the logic presented was like this: - We (the OpenAI safety people) want to be able to have insight into what o1 is actually thinking, not a self-censored "people are watching me" version of its thinking. - o1 knows all kinds of potentially harmful information, like how to make bombs, how to cook meth, how to manipulate someone, etc, which could "cause harm" if seen by an end-user So the options as they saw it were: 1. RLHF both the internal thinking and the final output. In this case the thought process would avoid saying things that might "cause harm", and so could be shown to the user. But they would have a less clear picture of what the LLM was "actually" thinking, and the potential state space of exploration would be limited due to the self-censorship. 2. Only RLHF the final output. In this case, they can have a clearer picture into what the LLM is "actually" thinking (and the LLM could potentially explore the state space more fully without risking about causing harm), but thought process could internally mention things which they don't want the user to see. OpenAI went with #2. Not sure what DeepSeek has done -- whether they have RLHF'd the CoT as well, or just not worried as much about it.
fibers 2y ago
how many reported cases of banning are there? that sounds insane for asking it to print out its chain of thought
d3nj4l 2y ago
I have a lot of fun just posting a function into R1, saying "Improve this" and reading the chain of thought. Lots of insight in there that I would usually miss or glance over.
satvikpendem 2y ago
This is generally how I use LLMs anyway, as brainstorming tools, rather than writing code.
emporas 2y ago
I tried a month back o1 and Qwen with chain of thought QwQ, to explain to me some chemical reactions, QwQ got it correct, and o1 got it wrong. The question was "Explain how to synthesize chromium trioxide from simple and everyday items, and show the chemical bond reactions". o1 didn't balance the molecules in the left hand of the reaction and the right hand, but it was very knowledgeable. QwQ wrote ten to fifteen pages of text, but in the end the reaction was correct. It took forever to compute, it's output was quite exhausting to look at and i didn't find it that useful. Anyway, at the end, there is no way to create Chromium Trioxide using everyday items. I thought maybe i could mix some toothpaste and soap and get it.

simonw 2y ago

Yeah, it is definitely a big deal. I expect it will be a net positive: they proved that you can both train and run inference against powerful models for way less compute than people had previously expected - and they published enough details that other AI labs are already starting to replicate their results. I think this will mean cheaper, faster, and better models. This FAQ about it is very good: https://stratechery.com/2025/deepseek-faq/ https://stratechery.com/2025/deepseek-faq/

startupsfail 2y ago
This may mean that $3k/task on some benchmarks published by OpenAI are now at slightly lower price tag. It is possible however that OpenAI was using similar level acceleration in the first place, they’ve just not published the details. And a few engineers left and replicated (or even bested it) in a new lab. Overall, it’s a good boost, modern software is getting a better fit into new generation of hardware and is performing faster. Maybe we should pay more attention when NVIDIA is publishing their N-times faster ToPS numbers, and not completely dismissing it as marketing.
netdevphoenix 2y ago
Why did DeepSeek not kept this for themselves? Is this a Meta style scorched earth strategy?
- deleted 2y ago
  [deleted]
- simonw 2y ago
  There are a bunch of theories floating round. Personally this looks to me like an ego thing: the DeepSeek team are really, really good and their CEO is enjoying the enormous attention they are getting, plus the pride of proving that Chinese AI labs can take the lead in a field that everyone thought the USA was unassailable in. Maybe they are true believers in building and sharing "AGI" with the world? Lots of people see this as a Chinese government backed conspiracy to undermine the US AI industry. I'm not sure how credible that idea is. I saw somewhere (though I've not confirmed it with a second source) that none of the people listed on the DeepSeek papers got educated at US universities - they all went to school in China, which further emphasizes how good China's home-grown talent pool has got.

pavitheran 2y ago

Deepseek is a big deal but we should be happy not worried that our tools are improving.

bbzealot 2y ago
Why though? I'm worried these technologies may take my job away and make the balance between capital and labor even more uneven. Why should I be happy?
- CamperBob2 2y ago
  You won't be happy doing a robot's job either, at least not for long. In the ideal case, we won't be dependent on the unwilling labor of other humans at all. Would you do your current job for free? If not -- if you'd rather do something else with your productive life -- then it seems irrational to defend the status quo. One thing's for certain: ancient Marxist tropes about labor and capital don't bring any value to the table. Abandon that thinking sooner rather than later; it won't help you navigate what's coming.
  - hooverd 2y ago
    Because billionaires think that you are a horse and that the best course of action is to turn you into glue while they hope AGI lets them live forever.
    - CamperBob2 2y ago
      Billionaires don't think about you at all. That's what nobody seems to get. We enjoy many luxuries unavailable even to billionaires only a few decades ago. For this trend to continue, the same thing needs to happen in other sectors that happened in (for example) the agricultural sector over the course of the 20th century: replacement of human workers by mass automation and superior organization.
      - p_j_w 2y ago

GaggiX 2y ago

DeepSeek R1 is o1 but free to use, open source, and also distilled on different models, even the ones that could run on your phone so yeah.

csomar 2y ago

Everyone else should rejoice. OpenAI is probably cooked, however. Nvidia might be cooked too.

snowram 2y ago
Is Nvidia really cooked? If this new RF tech does scale, couldn't a bigger model be made that would require more compute power for training and inference?
- cool_dude85 2y ago
  Imagine an s-curve relating capital expenditure on compute and "performance" as the y-axis. It's possible that this does not change the upper bound of the s-curve but just shifts the performance gains way to the left. Such a scenario would wipe out a huge amount of the value of Nvidia.
  - treis 2y ago
    I don't think it matters much to Nvidia so long as they're the market leader. If AI gets cheaper to compute it just changes who buys. Goes from hyperscalers to there being an AI chip in every phone, tablet, laptop, etc. still lots and lots of money to be made.
- swfsql 2y ago
  I read around that DeepSeek's team managed to work-around hardware limitations, and that in theory goes against the "gatekeeping" or "frontrunning" investment expectations from nvidia. If a partial chunk of investment is a bet on those expectations, that would explain a part of the stock turbulence. I think their 25x inference price reduction vs openai is what really affected everything, besides the (uncertain) training cost reduction.
  - BeefWellington 2y ago
    We all use PCs and heck even phones that have thousands of times the system memory of the first PCs. Making something work really efficiently on older hardware doesn't necessarily imply less demand. If those lessons can be taken and applied to newer generations of hardware, it would seem to make the newer hardware all the more valuable.

coliveira 2y ago

It depends on the problem type. If your problem requires math reasoning, deepSeek response is quite impressive and surpasses what most people can do in a single session.

horsawlarway 2y ago

I would say worry? Yes. Panic? No. It's... good. Even the qwen/llama distills are good. I've been running the Llama-70b-distill and it's good enough that it mostly replaces my chatgpt plus plan (not pro - plus). I think if anything - One of my big takeaways is that OpenAI shot themselves in the foot, big time, by not exposing the COT for the O1 Pro models. I find the <think></think> section of the DeepSeek models to often be more helpful than the actual answer. For work that's treating the AI as collaborative rather than "employee replacement" the COT output is really valuable. It was a bad move for them to completely hide it from users, especially because they make the user sit there waiting while it generates anyways.

flmontpetit 2y ago

As far as realizing the prophecy of AI as told by its proponents and investors goes, probably not. LLMs still have not magically transcended their obvious limitations. However this has huge implications when it comes to the feasibility and spread of the technology, and further implications with regards to economy and geopolitics now that confidence in the American AI sector has been hit and people and organizations internationally have somewhere else to look for. edit: That being said, this is the first time I've seen a LLM do a better job than even a senior expert could do, and even if it's on small scope/in a limited context, it's becoming clear that developers are going to have to adopt this tech in order to stay competitive.

buyucu 2y ago

There are two things. First, deepseek v3 and r1 are both amazing models. Second, the fact that deepseek was able to pull this off with such modest resources is an indication that there is no moat, and you might wake up tomorrow and find an even better model from a company you have never heard of.

girvo 2y ago
Pull this off with such modest resources, including using ChatGPT itself for its RL inputs. It’s quite smart, and doesn’t disagree with your point that there is no moat per se, but without those frontier models and their outputs there is no V3, there is no R1.
- buyucu 2y ago
  this is how science works.

steeeeeve 2y ago

Today it is. Tomorrow everyone will look at it like Wish or Temu.

ryao 2y ago
This seems relevant: https://finance.yahoo.com/news/deepseek-temu-ai-analysts-132500040.html https://finance.yahoo.com/news/deepseek-temu-ai-analysts-132... People are already looking at it like Temu.

llm_trw 2y ago

End result is on par with o1 preview, which is ironically more intelligent than o1, but the intermediate tokens are actually useful. I've got it running locally last night and out of 50 questions so far I've gotten the answer in the chain of thought in more than half.